The conjunction of knowledge discovery and multimedia documents presents a very important challenge. This new field of knowledge discovery in multimedia documents, dealing with non-structured information such as texts, images, videos, audio and virtual data, requires the collaboration of experts in many areas of interest revolving around document management systems, data mining, visual computing, signal processing, multimedia data and machine learning. This work brings together experts in digital media content analysis, state-of-art data mining and knowledge discovery in multimedia database systems, knowledge engineers and domain experts from diverse applied disciplines. Multimedia documents are ubiquitous and often required, if not essential, in many applications today. This phenomenon has made multimedia documents widespread and extremely large. There are tools for managing and searching within these collections, but the need for tools to extract hidden useful knowledge embedded within multimedia objects is becoming pressing and central for many decision-making applications. The tools needed today are tools for discovering relationships between objects or segments within multimedia document components, such as classifying images based on their content, extracting patterns in sound, categorizing speech and music and recognizing and tracking objects in video streams.